Racial Disparities in Breast Cancer Presentation and Diagnosis in COVID-Era Central Texas.

INTRODUCTION: The COVID-19 pandemic has significantly impacted the diagnosis of breast cancer (BC). With a large Hispanic/Latinx population, early revocation of mask mandates, and lower vaccination rate than many other states, this study explores the relationship between COVID-19 and the presentation and diagnosis of BC patients in the unique socio-politico-economic context of Central Texas. METHODS: This study is a retrospective review of the Seton Medical Center Austin tumor registry for BC patients from March 1, 2019 to March 2, 2021. We compared demographics, insurance status, clinical and pathologic stage, and time from diagnosis to intervention between "pre-COVID" (March 1, 2019- March 1, 2020) and "post-COVID" (March 2, 2020-March 2, 2021). We utilized descriptive, univariate, and multivariable logistic regression statistics. RESULTS: There were 781 patients diagnosed with BC, with 113 fewer post-COVID compared to pre-COVID. The proportion of Black patients diagnosed with BC decreased post-COVID compared with pre-COVID (10.1%-4.5%, P = 0.002). When adjusting for other factors, uninsured and underinsured patients had increased odds of presenting with late-stage BC (odds ratio:5.40, P < 0.001). There was also an association between presenting with stage 2 or greater BC and delayed time-to-intervention. CONCLUSIONS: Although fewer women overall were diagnosed with BC post-COVID, the return to baseline diagnoses has yet to be seen. We identified a pandemic-related decrease in BC diagnoses in Black women and increased odds of late-stage cancer among uninsured patients, suggesting a disparate relationship between COVID-19 and health care access and affordability. Outreach and screening efforts should address strategies to engage Black and uninsured patients.

Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast.

PURPOSE: A method is presented to select the optimal time points at which to measure DCE-MRI signal intensities, leaving time in the MR exam for high-spatial resolution image acquisition. THEORY: Simplicial complexes are generated from the Kety-Tofts model pharmacokinetic parameters Ktrans and ve . A geometric search selects optimal time points for accurate estimation of perfusion parameters. METHODS: The DCE-MRI data acquired in women with invasive breast cancer (N = 27) were used to retrospectively compare parameter maps fit to full and subsampled time courses. Simplicial complexes were generated for a fixed range of Kety-Tofts model parameters and for the parameter ranges weighted by estimates from the fully sampled data. The largest-area manifolds determined the optimal three time points for each case. Simulations were performed along with retrospectively subsampled data fits. The agreement was computed between the model parameters fit to three points and those fit to all points. RESULTS: The optimal three-point sample times were from the data-informed simplicial complex analysis and determined to be 65, 204, and 393 s after arrival of the contrast agent to breast tissue. In the patient data, tumor-median parameter values fit using all points and the three selected time points agreed with concordance correlation coefficients of 0.97 for Ktrans and 0.67 for ve . CONCLUSION: It is possible to accurately estimate pharmacokinetic parameters from three properly selected time points inserted into a clinical DCE-MRI breast exam. This technique can provide guidance on when to capture images for quantitative data between high-spatial-resolution DCE-MRI images.

Patient reported outcomes affecting quality of life in socioeconomically disadvantaged cancer patients.

PURPOSE: The aim of this study was to identify correlates of quality of life (QOL) for socioeconomically disadvantaged cancer patients receiving care in the "safety net" health system. DESIGN: This cross-sectional study used linear regressions to determine the effect of patient reported outcome measures (PRO) on QOL.Sample/Methods: Cancer patients (n = 115) receiving drug therapy completed a series of PROs including: Functional Assessment of Cancer Therapy (FACT-G), PROMIS (Anxiety, Depression, Fatigue, Pain Interference, and Physical Function), and the Comprehensive Score for Financial Toxicity. FINDINGS: More than 60% of patients reported an annual income below $24,999. Forty-five percent of patients were either uninsured or county-funded. Depression, pain, and financial toxicity were found to be consistently significant correlates of QOL.Implications: Cancer patients with existing financial strain have unique psychosocial stressors. This study provides insight into the relationship between these stressors, and the need for targeted screening and intervention that address such aspects of care.

Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting.

BACKGROUND: The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer. METHODS: Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (Ktrans) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with Ktrans and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves. RESULTS: Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, Ktrans, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR. CONCLUSIONS: Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI.

Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting.

This protocol describes a complete data acquisition, analysis and computational forecasting pipeline for employing quantitative MRI data to predict the response of locally advanced breast cancer to neoadjuvant therapy in a community-based care setting. The methodology has previously been successfully applied to a heterogeneous patient population. The protocol details how to acquire the necessary images followed by registration, segmentation, quantitative perfusion and diffusion analysis, model calibration, and prediction. The data collection portion of the protocol requires ~25 min of scanning, postprocessing requires 2-3 h, and the model calibration and prediction components require ~10 h per patient depending on tumor size. The response of individual breast cancer patients to neoadjuvant therapy is forecast by application of a biophysical, reaction-diffusion mathematical model to these data. Successful application of the protocol results in coregistered MRI data from at least two scan visits that quantifies an individual tumor's size, cellularity and vascular properties. This enables a spatially resolved prediction of how a particular patient's tumor will respond to therapy. Expertise in image acquisition and analysis, as well as the numerical solution of partial differential equations, is required to carry out this protocol.

Characterizing Errors in Pharmacokinetic Parameters from Analyzing Quantitative Abbreviated DCE-MRI Data in Breast Cancer.

This study characterizes the error that results when performing quantitative analysis of abbreviated dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data of the breast with the Standard Kety-Tofts (SKT) model and its Patlak variant. More specifically, we used simulations and patient data to determine the accuracy with which abbreviated time course data could reproduce the pharmacokinetic parameters, Ktrans (volume transfer constant) and ve (extravascular/extracellular volume fraction), when compared to the full time course data. SKT analysis of simulated abbreviated time courses (ATCs) based on the imaging parameters from two available datasets (collected with a 3T MRI scanner) at a temporal resolution of 15 s (N = 15) and 7.23 s (N = 15) found a concordance correlation coefficient (CCC) greater than 0.80 for ATCs of length 3.0 and 2.5 min, respectively, for the Ktrans parameter. Analysis of the experimental data found that at least 90% of patients met this CCC cut-off of 0.80 for the ATCs of the aforementioned lengths. Patlak analysis of experimental data found that 80% of patients from the 15 s resolution dataset and 90% of patients from the 7.27 s resolution dataset met the 0.80 CCC cut-off for ATC lengths of 1.25 and 1.09 min, respectively. This study provides evidence for both the feasibility and potential utility of performing a quantitative analysis of abbreviated breast DCE-MRI in conjunction with acquisition of current standard-of-care high resolution scans without significant loss of information in the community setting.

The rate of breast fibroglandular enhancement during dynamic contrast-enhanced MRI reflects response to neoadjuvant therapy.

PURPOSE: This study assesses the rate of enhancement of breast fibroglandular tissue after administration of a magnetic resonance imaging (MRI) gadolinium-based contrast agent and determines its relationship with response to neoadjuvant therapy (NAT) in women with breast cancer. METHOD: Women with locally advanced breast cancer (N = 19) were imaged four times over the course of NAT. Dynamic contrast-enhanced (DCE) MRI was acquired after administration of a gadolinium-based contrast agent with a temporal resolution of 7.27 s. The tumor, fibroglandular tissue, and adipose tissue were semi-automatically segmented using a manually drawn region of interest encompassing the tumor followed by fuzzy c-means clustering. The rate and relative intensity of signal enhancement were calculated for each voxel within the tumor and fibroglandular tissue. RESULTS: The rate of fibroglandular tissue enhancement after contrast agent injection declined by an average of 29 % over the course of NAT. This decline was present in 16 of the 19 patients in the study. The rate of enhancement is significantly higher in women who achieve pathological complete response (pCR) after both 1 cycle (68 % higher, p < 0.05) and after 3-5 cycles of NAT (58 % higher; p < 0.05). The relative intensity of fibroglandular enhancement correlates with the rate of enhancement (R2 = 0.64, p < 0.001) and is higher in women who achieve pCR after both 1 cycle and after 3-5 cycles of NAT (p < 0.05, both timepoints). CONCLUSION: The rate of fibroglandular tissue enhancement declines over the course of therapy, provides novel information not reflected by tumoral measures, and may predict pathological response early in the course of therapy, with smaller declines in enhancement in women who achieve favorable response.

Evaluating patient-specific neoadjuvant regimens for breast cancer via a mathematical model constrained by quantitative magnetic resonance imaging data.

The ability to accurately predict response and then rigorously optimize a therapeutic regimen on a patient-specific basis, would transform oncology. Toward this end, we have developed an experimental-mathematical framework that integrates quantitative magnetic resonance imaging (MRI) data into a biophysical model to predict patient-specific treatment response of locally advanced breast cancer to neoadjuvant therapy. Diffusion-weighted and dynamic contrast-enhanced MRI data is collected prior to therapy, after 1 cycle of therapy, and at the completion of the first therapeutic regimen. The model is initialized and calibrated with the first 2 patient-specific MRI data sets to predict response at the third, which is then compared to patient outcomes (N = 18). The model's predictions for total cellularity, total volume, and the longest axis at the completion of the regimen are significant within expected measurement precision (P< 0.05) and strongly correlated with measured response (P < 0.01). Further, we use the model to investigate, in silico, a range of (practical) alternative treatment plans to achieve the greatest possible tumor control for each individual in a subgroup of patients (N = 13). The model identifies alternative dosing strategies predicted to achieve greater tumor control compared to the standard of care for 12 of 13 patients (P < 0.01). In summary, a predictive, mechanism-based mathematical model has demonstrated the ability to identify alternative treatment regimens that are forecasted to outperform the therapeutic regimens the patients clinically. This has important implications for clinical trial design with the opportunity to alter oncology care in the future.

Evaluation of the use of non-formulary oncology medications restricted to outpatient use in hospitalized patients after implementation of a criteria-for-use algorithm.

OBJECTIVE: To decrease the number of orders and total hospital spend for inpatient use of antineoplastic drugs of interest, while evaluating each case for urgent or emergent need for administration. METHODOLOGY: This study is a multicenter, retrospective, cost-evaluation, cohort study performed in five Ascension Seton hospitals in the Austin, Texas area between 1 January 2013 and 31 December 2018. Patients were identified via a dispense analysis report for the antineoplastic drugs of interest. RESULTS: An overall reduction of 56% was seen in orders processed with a 62% decrease in annual hospital spending after implementation of the criteria-for-use algorithm. When results were evaluated without including rituximab orders, a reduction of 17% was seen in orders processed with a 21% decrease in annual hospital spending. DISCUSSION AND CONCLUSION: The decreases in our primary outcomes were primarily driven by a reduction in the use of one drug, rituximab. Overall, implementation of a criteria-for-use algorithm was effective in reducing both overall number of orders and hospital spending for restricted antineoplastic agents.

Identification and Management of Iron Deficiency Anemia in the Emergency Department.

BACKGROUND: Iron deficiency anemia is the most common hematologic disorder in the United States and worldwide. Yet, clinical guidelines for the identification and management of this disorder in the emergency department are lacking. OBJECTIVE OF REVIEW: This clinical review examines strategies for identifying and treating iron deficiency anemia in the emergency department, with a focus on the role of oral iron therapy, intravenous iron therapy, as well as red blood cell transfusion. The article highlights both the available evidence on this topic and the need for future research. DISCUSSION: The diagnosis of iron deficiency anemia has important clinical implications and, although testing is generally straightforward, it may be under-recognized. The scant literature available describing emergency department practice patterns for iron deficiency anemia suggests there is room for improvement. In particular, intravenous iron may be underutilized and red blood cell transfusions administered too liberally. CONCLUSIONS: Iron deficiency anemia is common and many patients can be treated effectively with oral iron. For selected patients with moderate-to-severe iron deficiency anemia, intravenous iron is safe and more effective than oral iron. Red blood cell transfusions should be used rarely for hemodynamically stable patients with iron deficiency irrespective of hemoglobin levels.

Recent trends in the age at diagnosis of colorectal cancer in the US National Cancer Data Base, 2004-2015.

BACKGROUND: The incidence of colorectal cancer (CRC) in adults younger than 50 years has increased in the United States over the past decades according to Surveillance, Epidemiology, and End Results data. National guidelines conflict over beginning screening at the age of 45 or 50 years. METHODS: This was a retrospective study of National Cancer Data Base data from 2004 to 2015. The Cochran-Armitage test for trend was used to assess changes in the proportion of cases diagnosed at an age younger than 50 years. RESULTS: This study identified 130,165 patients diagnosed at an age younger than 50 years and 1,055,598 patients diagnosed at the age of 50 years or older. The proportion of the total number of patients diagnosed with CRC at an age younger than 50 years rose (12.2% in 2015 vs 10.0% in 2004; P < .0001). Younger adults presented with more advanced disease (stage III/IV; 51.6% vs 40.0% of those 50 years old or older). Among men, diagnosis at ages younger than 50 years rose only in non-Hispanic whites (P < .0001), whereas among women, Hispanic and non-Hispanic whites had increases in younger diagnoses over time (P < .05). All income quartiles had a proportional increase in younger adults over time (P < .001), with the highest income quartile having the highest proportion of younger cases. The proportion of younger onset CRC cases rose in urban areas (P < .001) but did not rise in rural areas. CONCLUSIONS: The proportion of persons diagnosed with CRC at an age younger than 50 years in the United States has continued to increase over the past decade, and younger adults present with more advanced disease. These data should be considered in the ongoing discussion of screening guidelines.

Stereotactic Vertebroplasty for Spinal Metastases with Multilevel Bilateral Pedicle Fractures: A Technical Note.

Vertebral compression fractures (VCFs) represent a significant cause of disability and primarily result from either underlying vertebral body neoplasms or osteoporosis. Vertebroplasty (VP) is a procedure commonly utilized to repair pathologic VCFs in order to manage pain and reinstate vertebral body height. However, there is a paucity of literature on how to manage painful multilevel VCFs with concomitant bilateral pedicle fractures. We describe a patient with a primary prostatic carcinoma and VCFs of the third and fourth lumbar vertebrae (L3 and L4, respectively) with concomitant bilateral pedicle fractures secondary to metastatic disease. Due to the degree of damage to the L3 and L4 vertebral bodies and pedicles, a VP performed via a percutaneous approach was deemed to be too high risk. VP for L3 and L4 was instead performed by utilizing stereotactic spine navigation and an intraoperative O-arm (Medtronic Corporation, Minneapolis, Minnesota). Our result indicates a potential role for stereotactic spine navigation in vertebroplasty for complex pathologic VCFs.

Magnetization Transfer MRI of Breast Cancer in the Community Setting: Reproducibility and Preliminary Results in Neoadjuvant Therapy.

Repeatability and reproducibility of magnetization transfer magnetic resonance imaging of the breast, and the ability of this technique to assess the response of locally advanced breast cancer to neoadjuvant therapy (NAT), are determined. Reproducibility scans at 3 different 3 T scanners, including 2 scanners in community imaging centers, found a 16.3% difference (n = 3) in magnetization transfer ratio (MTR) in healthy breast fibroglandular tissue. Repeatability scans (n = 10) found a difference of ∼8.1% in the MTR measurement of fibroglandular tissue between the 2 measurements. Thus, MTR is repeatable and reproducible in the breast and can be integrated into community imaging clinics. Serial magnetization transfer magnetic resonance imaging performed at longitudinal time points during NAT indicated no significant change in average tumoral MTR during treatment. However, histogram analysis indicated an increase in the dispersion of MTR values of the tumor during NAT, as quantified by higher standard deviation (P = .005), higher full width at half maximum (P = .02), and lower kurtosis (P = .02). Patients' stratification into those with pathological complete response (pCR; n = 6) at the conclusion of NAT and those with residual disease (n = 9) showed wider distribution of tumor MTR values in patients who achieved pCR after 2-4 cycles of NAT, as quantified by higher standard deviation (P = .02), higher full width at half maximum (P = .03), and lower kurtosis (P = .03). Thus, MTR can be used as an imaging metric to assess response to breast NAT.

Repeatability, reproducibility, and accuracy of quantitative mri of the breast in the community radiology setting.

BACKGROUND: Quantitative diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) have the potential to impact patient care by providing noninvasive biological information in breast cancer. PURPOSE/HYPOTHESIS: To quantify the repeatability, reproducibility, and accuracy of apparent diffusion coefficient (ADC) and T1 -mapping of the breast in community radiology practices. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: Ice-water DW-MRI and T1 gel phantoms were used to assess accuracy. Normal subjects (n = 3) and phantoms across three sites (one academic, two community) were used to assess reproducibility. Test-retest analysis at one site in normal subjects (n = 12) was used to assess repeatability. FIELD STRENGTH/SEQUENCE: 3T Siemens Skyra MRI quantitative DW-MRI and T1 -mapping. ASSESSMENT: Quantitative DW-MRI and T1 -mapping parametric maps of phantoms and fibroglandular and adipose tissue of the breast. STATISTICAL TESTS: Average values of breast tissue were quantified and Bland-Altman analysis was performed to assess the repeatability of the MRI techniques, while the Friedman test assessed reproducibility. RESULTS: ADC measurements were reproducible across sites, with an average difference of 1.6% in an ice-water phantom and 7.0% in breast fibroglandular tissue. T1 measurements in gel phantoms had an average difference of 2.8% across three sites, whereas breast fibroglandular and adipose tissue had 8.4% and 7.5% average differences, respectively. In the repeatability study, we found no bias between first and second scanning sessions (P = 0.1). The difference between repeated measurements was independent of the mean for each MRI metric (P = 0.156, P = 0.862, P = 0.197 for ADC, T1 of fibroglandular tissue, and T1 of adipose tissue, respectively). DATA CONCLUSION: Community radiology practices can perform repeatable, reproducible, and accurate quantitative T1 -mapping and DW-MRI. This has the potential to dramatically expand the number of sites that can participate in multisite clinical trials and increase clinical translation of quantitative MRI techniques for cancer response assessment. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Demonstrating Higher Incidence of Advanced Breast Malignancies in Our Young Hispanic Population.

Historically, the Hispanic population in the United States has had a lower incidence of cancer than the matched non-Hispanic population, despite disparities in access to health care, screening, and prevention. Our experience in Austin, Texas, directly contradicts this. We have seen a disproportionate amount of young Hispanic patients with advanced malignancies, particularly of the breast. The aim of this study was to compare the incidence of advanced breast malignancies. We performed a retrospective review over a 10-year period (2003-2013) of all newly diagnosed breast cancer patients. Data were collected from the cancer registry. Patients were divided into two groups: Hispanic versus non-Hispanic descent, with a subgroup of those aged less than 50 years. Primary outcome was the incidence of advanced cancers (stage 3 or 4). There were a total of 3968 breast cancer patients seen in our Shivers Cancer Center from 2003 to 2013, with an overall incidence of advanced breast cancer of 11.5 per cent. Of the patients aged less than 50 years, 14.2 per cent had advanced breast cancer. However, the rate among Hispanic patients was 21.3 per cent, whereas in non-Hispanic patients it was 13.5 per cent, P = 0.002. Being Hispanic was found to be an independent predictor of having advanced malignancies at a young age (odds ratio 1.7, confidence interval 1.1-2.5, P = 0.01). Here in Austin, Texas, we have found a higher overall incidence of breast cancer among young Hispanic women. This is important to recognize because more efforts may be required to increase screening and health-care access to this population.

Dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted magnetic resonance imaging for predicting the response of locally advanced breast cancer to neoadjuvant therapy: a meta-analysis.

This meta-analysis assesses the prognostic value of quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI) performed during neoadjuvant therapy (NAT) of locally advanced breast cancer. A systematic literature search was conducted to identify studies of quantitative DCE-MRI and DW-MRI performed during breast cancer NAT that report the sensitivity and specificity for predicting pathological complete response (pCR). Details of the study population and imaging parameters were extracted from each study for subsequent meta-analysis. Metaregression analysis, subgroup analysis, study heterogeneity, and publication bias were assessed. Across 10 studies that met the stringent inclusion criteria for this meta-analysis (out of 325 initially identified studies), we find that MRI had a pooled sensitivity of 0.91 [95% confidence interval (CI), 0.80 to 0.96] and specificity of 0.81(95% CI, 0.68 to 0.89) when adjusted for covariates. Quantitative DCE-MRI exhibits greater specificity for predicting pCR than semiquantitative DCE-MRI ([Formula: see text]). Quantitative DCE-MRI and DW-MRI are able to predict, early in the course of NAT, the eventual response of breast tumors, with a high level of specificity and sensitivity. However, there is a high degree of heterogeneity in published studies highlighting the lack of standardization in the field.

A phase I study of temsirolimus and thoracic radiation in non--small-cell lung cancer.

BACKGROUND: The addition of targeted agents to thoracic radiation has not improved outcomes in patients with locally advanced non-small-cell lung cancer (NSCLC). To improve cure rates in locally advanced NSCLC, effective targeted therapies need to be identified that can be given safely with radiation therapy. Temsirolimus is an inhibitor of the mammalian target of rapamycin (mTOR) pathway and has single-agent activity in lung cancer. Inhibition of the mTOR pathway has been found to augment the cytotoxic effect of radiation in preclinical studies. There is scant clinical experience with mTOR inhibitors and radiation. PATIENTS AND METHODS: This was a phase I study evaluating the combination of temsirolimus with thoracic radiation in patients with NSCLC. RESULTS: Ten patients were enrolled in the study. The dose-limiting toxicities included sudden death, pneumonitis, and pulmonary hemorrhage. The maximum tolerated dose of temsirolimus that could be administered safely with concurrent radiotherapy (35 Gy in 14 daily fractions) was 15 mg intravenously weekly. Of the 8 evaluable patients, 3 had a partial response and 2 had stable disease. CONCLUSION: The combination of temsirolimus 15 mg weekly and thoracic radiation is well tolerated and warrants further investigation, perhaps in a molecularly defined subset of patients.

MicroRNA profiling and prediction of recurrence/relapse-free survival in stage I lung cancer.

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. MicroRNAs (miRNAs) are a class of small non-coding RNAs of 19-25 nt and play important roles in gene regulation in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis of stage I NSCLC. MiRNAs extracted from 527 stage I NSCLC patients were profiled on the human miRNA expression profiling v2 panel (Illumina). The expression profiles were analyzed for their association with cancer subtypes, lung cancer brain metastasis and recurrence/relapse free survival (RFS). MiRNA expression patterns between lung adenocarcinoma and squamous cell carcinoma differed significantly with 171 miRNAs, including Let-7 family members and miR-205. Ten miRNAs associated with brain metastasis were identified including miR-145*, which inhibit cell invasion and metastasis. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 34 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype, whereas the second containing 27 miRNAs was adenocarcinoma specific. Both signatures were validated using formalin-fixed paraffin embedded and/or fresh frozen tissues in independent data set with 170 stage I patients. Our findings have important prognostic or therapeutic implications for the management of stage I lung cancer patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease.